Job description
Join a premier mathematics research team focused on advancing theory and its real-world applications. This full-time role offers an opportunity to collaborate across disciplines, publish in top journals, and contribute to impactful projects in data science, optimization, and mathematical modeling.
We seek a talented mathematician who combines rigorous analytical thinking with practical programming skills to solve complex problems and deliver measurable outcomes. The position is based in Cambridge, MA, with a flexible hybrid work policy to support collaboration with cross-functional teams.
Responsibility
- Develop and implement mathematical models to address real-world problems in data science, optimization, and scientific computing.
- Design experiments and simulations to validate models and quantify uncertainties.
- Collaborate with data scientists, engineers, and domain experts to translate theory into actionable insights.
- Publish research findings in peer-reviewed journals and present at conferences.
- Create robust, reproducible code in Python/R/Julia and maintain high-quality documentation.
- Mentor junior researchers and support grant proposals with rigorous mathematical justification.
- Lead or contribute to interdisciplinary projects with clear milestones and deliverables.
- Contribute to statistical analysis, hypothesis testing, and interpretation of results for stakeholders.
Qualification
- PhD or relevant Master’s in Mathematics, Applied Mathematics, Statistics, or a closely related field.
- Strong foundation in mathematical modeling, numerical methods, probability, and statistics.
- Proficiency in Python (NumPy/SciPy), R, and at least one scientific computing language (Julia, MATLAB).
- Experience with data analysis, visualization, and communicating complex results to non-technical audiences.
- Proven track record of research excellence and publications (or equivalent project portfolio).
- Excellent problem-solving skills, attention to detail, and ability to work independently and in teams.
- Strong written and verbal communication skills; ability to explain abstract concepts clearly.
- Familiarity with LaTeX, Git, and collaborative research workflows.